.png){kind=icon}
返回
MDVSCEfficient Wireless Model Division Video Semantic Communication
.png){kind=icon}
PRE
AI
DOI：10.1109/JIOT.2024.3464614.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
This article introduces a novel method for transmitting video data over noisy wireless channels with high efficiency and controllability. The method derivates from model division multiple access (MDMA) to extract common semantic features from video frames. It also uses deep joint source-channel coding (JSCC) as the main framework to establish communication links and deal with channel noise. An entropy-based semantic importance coding scheme is developed to adjust the data amount accurately and explicitly. We name our method as model division video semantic communication (MDVSC). The main steps of our approach are as follows: first, video frames are transformed into a latent space to reduce computational complexity and redistribute data. Then, common features and individual features are extracted, and semantic importance coding is applied to further eliminate redundant semantic information under the communication bandwidth constraint. We evaluate our method on standard video test sequences and compare it with traditional wireless video coding methods. The results show that MDVSC generally surpasses the conventional methods in terms of quality metrics and has the capability to control code length precisely. Moreover, additional experiments and ablation studies are conducted to demonstrate its potential for various tasks.
Keyword:
Semantics
Encoding
Feature extraction
Wireless communication
Channel coding
Streaming media
Bandwidth
Joint source-channel coding (JSCC)
latent transform
model division multiple access (MDMA)
semantic coding
semantic communications
video transmission
期刊
IF:
8.9
论文数:
1.4W
被引数:
7.8W
机构
引用论文
.png){kind=icon}
分享收藏分享收藏Rethinking Modern Communication from Semantic Coding to Semantic Communication从语义编码到语义通信的现代通信再思考
OAAI
OAAI分享收藏
查看更多内容